One place for data labeling, data management, and data science
Unify in-house and external labeling activities with flexible labeling interfaces and work distribution tools. Manage all of your labeled data in one place. Supercharge data science work with pre-built integrations and the latest ML techniques.
Create better training data
An ML model is only as good as its training data. Take control of training data quality through collaborative labeling and quality assurance processes.
Spend more time building AI
Say goodbye to those spreadsheets and python scripts. Labelbox is a complete set of tools to create and manage training data. Now you can get back to creating the products your customers want.
Extensible and Developer Friendly
Set up ingest, ETL, and egress integrations between your ML pipeline and Labelbox. Connect your ML models to supercharge labeling productivity and orchestrate active learning. Labelbox is API-first so you can do just about anything!
from graphqlclient import GraphQLClient
client = GraphQLClient('https://api.labelbox.com/graphql')
client.inject_token('Bearer <API_KEY_HERE>')
data = client.execute('
mutation {
createDataRow(
data: {
rowData: "<DATA_THAT_NEEDS_TO_BE_LABELED>",
dataset: {
connect: {
id: "<DATASET_ID_HERE>"
}
},
organization: {
connect: {
id: "<INSERT_YOUR_ORGANIZATION_ID_FROM_ABOVE_HERE>"
}
},
}
)
}
')
from graphqlclient import GraphQLClient
client = GraphQLClient('https://api.labelbox.com/graphql')
client.inject_token('Bearer <API_KEY_HERE>')
data = client.execute('
mutation {
createLabel(
data: {
label:"<INSERT_LABEL_DATA_STRING_HERE>",
secondsToLabel: 42,
dataRow: {
connect: {
id: "<INSERT_DATA_ROW_ID_HERE>"
}
},
project: {
connect: {
id: "<INSERT_PROJECT_ID_HERE>"
}
},
type: {
connect: {
name: "Any"
}
}
}) {
id
label
}}
')
from graphqlclient import GraphQLClient
client = GraphQLClient('https://api.labelbox.com/graphql')
client.inject_token('Bearer <API_KEY_HERE>')
data = client.execute('
mutation{
createPrediction(data:{
label:"<should-be-the-exact-same-as-label.label>",
predictionModelId:"<from-the-prediction-model-you-created-earlier>",
projectId:"<any-project-id>",
dataRowId:"<any-datarow-id>",
}){
id
}
}
')
from graphqlclient import GraphQLClient
client = GraphQLClient('https://api.labelbox.com/graphql')
client.inject_token('Bearer <API_KEY_HERE>')
data = client.execute('
query {
project(where:{id: "<INSERT_PROJECT_ID_HERE>"}) {
labels(first: 5){
id
label
createdBy{
id
email
}
type {
id
name
}
secondsToLabel
agreement
dataRow {
id
rowData
}
}
}
}
')
This is about managing institutional knowledge
Your AI is making critical business decions based on the training data it learns from. This training data is the instutional knowledge your busines depends on to deliver goods and services to your customers.
Maximize return on AI investment
Building AI is resource intensive. Yet, most of these resources are used to build and manage tools and infrastructure. Labelbox unifies data labeling, storage and management in one place, providing your team a robust foundation to focus on creating business value.
Customers ♥ Labelbox
Labelbox has become essential to our process. It is the beginning of every single deep learning exercise we do. The only thing that comes before Labelbox is recording the data.
Gal Ozery
AI Product Owner, Genius Sports
Labelbox is very well integrated as a part of our overall system design. Labelbox has helped us efficiently collect and analyze data through their strong infrastructure support. We’re able to get the labels we need for all different types of video and image analysis.
Stephen Krotosky
Manager, Applied Machine Learning